| **Arcee AFM-4.5B** | `arcee-ai/AFM-4.5B-Base` | Arcee's foundational model series for real world reliability and edge deployments. |

| **Persimmon** (8B) | `adept/persimmon-8b-chat` | Adept’s open 8B model with a 16K context window and fast inference; trained for broad usability and licensed under Apache 2.0. |

| **Solar** (10.7B) | `upstage/SOLAR-10.7B-Instruct-v1.0` | Upstage's 10.7B parameter model, optimized for instruction-following tasks. This architecture incorporates a depth-up scaling methodology, enhancing model performance. |

| **Tele FLM** (52B-1T) | `CofeAI/Tele-FLM` | BAAI & TeleAI's multilingual model, available in 52-billion and 1-trillion parameter variants. It is a decoder-only transformer trained on ~2T tokens |

| **Ling** (16.8B–290B) | `inclusionAI/Ling-lite`, `inclusionAI/Ling-plus` | InclusionAI’s open MoE models. Ling-Lite has 16.8B total / 2.75B active parameters, and Ling-Plus has 290B total / 28.8B active parameters. They are designed for high performance on NLP and complex reasoning tasks. |

| **Granite 3.0, 3.1** (IBM) | `ibm-granite/granite-3.1-8b-instruct` | IBM's open dense foundation models optimized for reasoning, code, and business AI use cases. Integrated with Red Hat and watsonx systems. |

| **Granite 3.0 MoE** (IBM) | `ibm-granite/granite-3.0-3b-a800m-instruct` | IBM’s Mixture-of-Experts models offering strong performance with cost-efficiency. MoE expert routing designed for enterprise deployment at scale. |

| **Orion** (14B) | `OrionStarAI/Orion-14B-Base` | A series of open-source multilingual large language models by OrionStarAI, pretrained on a 2.5T token multilingual corpus including Chinese, English, Japanese, Korean, etc, and it exhibits superior performance in these languages. |

| **Llama Nemotron Super** (v1, v1.5, NVIDIA) | `nvidia/Llama-3_3-Nemotron-Super-49B-v1`, `nvidia/Llama-3_3-Nemotron-Super-49B-v1_5` | The [NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) family of multimodal models provides state-of-the-art reasoning models specifically designed for enterprise-ready AI agents. |

| **Llama Nemotron Ultra** (v1, NVIDIA) | `nvidia/Llama-3_1-Nemotron-Ultra-253B-v1` | The [NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) family of multimodal models provides state-of-the-art reasoning models specifically designed for enterprise-ready AI agents. |

| **NVIDIA Nemotron Nano 2.0** | `nvidia/NVIDIA-Nemotron-Nano-9B-v2` | The [NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) family of multimodal models provides state-of-the-art reasoning models specifically designed for enterprise-ready AI agents. `Nemotron-Nano-9B-v2` is a hybrid Mamba-Transformer language model designed to increase throughput for reasoning workloads while achieving state-of-the-art accuracy compared to similarly-sized models. |